Theorizing Improved NLP Features for Promoting Behavior that Supports CMC Users’ Subjective Well-Being

Authors

  • Sarah E. Cornwell The University of Western Ontario
  • Nicole S. Delellis University of Western Ontario
  • Dominique Kelly University of Western Ontario https://orcid.org/0000-0003-1222-6237
  • Yifan Liu University of Western Ontario
  • Alexander Mayhew University of Western Ontario
  • Yimin Chen The Royal Melbourne Institute of Technology
  • Victoria L. Rubin University of Western Ontario

DOI:

https://doi.org/10.29173/cais1937

Keywords:

Subjective Well-Being, Natural Language Processing, Computer Mediated Communication

Abstract

This work-in-progress identifies gaps in the current Natural Language Processing (NLP) approaches for pro-social communication detection by organizing the state-of-the-art NLP feature detection approaches according to models of Subjective Well-Being (SWB) from Positive Psychology. We need to better understand the current state of the field and what features of prosocial computer-mediated communication (CMC) we have yet to address. 

Théoriser les caractéristiques améliorées du NLP pour promouvoir un comportement qui favorise le bien-êtresubjectif des utilisateurs de communcation virtuelle

Résumé
Ce travail en cours identifie les lacunes dans l’approche actuelle de détection de la communication pro-social en organisant les approches de détection des caractéristiques de l’état de l’art NLP selon les modèles du bien-être subjectif (Subjective Well-being, SWB) en psychologie positive. Nous devons mieux comprendre l’état actuel du domaine et quelles caractéristiques de la communication prosociale assistée par ordinateur (computer-mediated communication, CMC) n’ont pas encore été abordées.

Mots-clés
bien-être subjectif; processus de langage naturel; communication prosociale assistée par ordinateur

References

Bao, J., Wu, J., Zhang, Y., Chandrasekharan, E., & D. Jurgens. (2021). Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations. In Proceedings of the Web Conference 2021 (WWW '21). Association for Computing Machinery, New York, NY, USA, 1134–1145. https://doi.org/10.1145/3442381.3450122

Davidson, T., Warmsley, D., Macy, M., & Weber, I. (2017). Automated Hate Speech Detection and the Problem of Offensive Language. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), 512-515. https://ojs.aaai.org/index.php/ICWSM/article/view/14955

Desmet, P. M. A., & Pohlmeyer, A. E. (2013). Positive design: An introduction to design for subjective well-being. International Journal of Design, 7(3), 5-19.

Diener, E. (1984). Subjective Well-Being. Psychological Bulletin, 95(3), 11–58. https://doi.org/10.1007/978-90-481-2350-6_2

Dinakar, K., Jones, B., Havasi, C., Lieberman, H., & Picard, R. (2012). Common sense reasoning for detection, prevention, and mitigation of cyberbullying. ACM Transactions on Interactive Intelligent Systems (TiiS), 2(3), 1-30.

Emmons, R.A., & McCullough, M.E. (2003). Counting blessings versus burdens: An experimental investigation of gratitude and subjective well-being in daily life. Journal of Personality and Social Psychology, 84, 377–389.

Grant, A. M., & Gino, F. (2010). A little thanks goes a long way: Explaining why gratitude expressions motivate prosocial behavior. Journal of personality and social psychology, 98(6), 946. https://doi.org/10.1037/a0017935

Heintzelman, S., & Tay, L. (2017). Subjective well-being: Payoffs of being happy and ways to promote happiness. Positive Psychology: Established and Emerging Issues (pp. 9–28). https://doi.org/10.4324/9781315106304

Hughes, M., Roy, B. C., & Roy, D. (2024). In Pursuit of Constructive Communication: Designing Tools to Support Development of Constructive Communication Metrics. Designing Interactive Systems Conference, 121–124. https://doi.org/10.1145/3656156.3663720

Kelly, D., Liu, Y., Mayhew, A., Chen, Y., Cornwel, S.E., Delellis, N.S. and Rubin, V.L. (2022), Supporting Prosocial Behaviour in Online Communities through Social Media Affordances. Proceedings of the Association for Information Science and Technology, 59: 723-725. https://doi.org/10.1002/pra2.703

Kern, M. L., Waters, L. E., Adler, A., & White, M. A. (2015). A multidimensional approach to measuring well-being in students: Application of the PERMA framework. The Journal of Positive Psychology, 10(3), 262-271. doi: 10.1080/17439760.2014.936962

Kiesling, S.F., Pavalanathan, U., Fitzpatrick, J., Han, X., & J. Eisenstein. (2018). Interactional Stancetaking in Online Forums. Computational Linguistics, 44 (4): 683–718. doi: https://doi.org/10.1162/coli_a_00334

Kjell, O. N. E., Sikström, S., Kjell, K., & Schwartz, H. A. (2022). Natural language analyzed with AI-based transformers predict traditional subjective well-being measures approaching the theoretical upper limits in accuracy. Scientific Reports, 12(1), 3918. https://doi.org/10.1038/s41598-022-07520-w

Liu, B. (2012). Sentiment analysis and opinion mining. Morgan & Claypool Publishers. Retrieved from http://www.cs.uic.edu/~liub/FBS/SentimentAnalysis-and-OpinionMining.html

Mayhew, A., Chen, Y., Cornwell, S.E., Delellis, N.S., Kelly, D., Liu, Y. and Rubin, V.L. (2022), Envisioning Ethical Mass Influence Systems. Proceedings of the Association for Information Science and Technology, 59: 756-758. https://doi.org/10.1002/pra2.716

Mirivel, J. C. (2019). Communication Behaviors That Make a Difference on Well-Being and Happiness. The Routledge handbook of positive communication: Contributions of an emerging community of research on communication for happiness and social change. https://doi.org/10.4324/9781315207759

Monge Roffarello, A., De Russis, L. & Pellegrino, M. (2024). Digital Wellbeing Lens: Design Interfaces That Respect User Attention. In Proceedings of the 2024 International Conference on Advanced Visual Interfaces (AVI '24). Association for Computing Machinery, New York, NY, USA, Article 51, 1–5. https://doi.org/10.1145/3656650.3656674

Norman, D. (2013). The design of everyday things. Basic Books.

Norrish, J. M., Williams, P., O'Connor, M., & Robinson, J. (2013). An applied framework for positive education. International Journal of Wellbeing, 3(2). 147-161. doi:10.5502/ijw.v3i2.2

Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135. https://doi.org/10.1561/1500000001

Penner, L. A., Dovidio, J. F., Piliavin, J. A., & Schroeder, D. A. (2005). Prosocial behavior: Multilevel perspectives. Annu. Rev. Psychol., 56, 365-392. https://doi.org/10.1146/annurev.psych.56.091103.070141

Qiao, D., Lee, S.-Y., Whinston, A., & Wei, Q. (2017). Incentive Provision and Pro-Social Behaviors. Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2017.675

Riva, G., Baños, R. M., Botella, C., Wiederhold, B. K., & Gaggioli, A. (2012). Positive technology: Using interactive technologies to promote positive functioning. Cyberpsychology, Behavior, and Social Networking, 15(2), 69-77. https://doi.org/10.1089/cyber.2011.0139

Sadagheyani, H. E., & Tatari, F. (2020). Investigating the role of social media on mental health. Mental health and social inclusion. https://doi.org/10.1108/MHSI-06-2020-0039

Saltz, E., Jalan, Z., & Acosta, T. (2024). Re-Ranking News Comments by Constructiveness and Curiosity Significantly Increases Perceived Respect, Trustworthiness, and Interest (arXiv:2404.05429). arXiv. https://doi.org/10.48550/arXiv.2404.05429

Sametoğlu, S., Pelt, D., Eichstaedt, J C., Ungar, L. H., & Bartels, M. (2022). The Value of Social Media Language for the Assessment of Wellbeing: A Systematic Review and Meta-Analysis [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/qnx2v

Seligman, M. (2011). Flourish: a visionary new understanding of happiness and well-being. Atria paperback.

Seligman, M. E., Ernst, R. M., Gillham, J., Reivich, K., & Linkins, M. (2009). Positive education: Positive psychology and classroom interventions. Oxford review of education, 35(3), 293-311. doi: 10.1080/03054980902934563

Tansey, T. N., Smedema, S., Umucu, E., Iwanaga, K., Wu, J.-R., Cardoso, E. da S., & Strauser, D. (2018). Assessing College Life Adjustment of Students With Disabilities: Application of the PERMA Framework. Rehabilitation Counseling Bulletin, 61(3), 131–142. https://doi.org/10.1177/0034355217702136

Treem, J. W., & Leonardi, P. M. (2012). Social media use in organizations: Exploring the affordances of visibility, editability, persistence, and association. Communication Yearbook, 36. http://dx.doi.org/10.2139/ssrn.2129853

Wagner, Gander, F., Proyer, R. T., & Ruch, W. (2019). Character Strengths and PERMA: Investigating the Relationships of Character Strengths with a Multidimensional Framework of Well-Being. Applied Research in Quality of Life, 15(2), 307–328. https://doi.org/10.1007/s11482-018-9695-z

Yoshimura, S. M., & Berzins, K. (2017). Grateful experiences and expressions: The role of gratitude expressions in the link between gratitude experiences and well-being. Review of Communication, 17(2), 106-118. https://doi.org/10.1080/15358593.2017.1293836

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Published

2025-05-23

How to Cite

Cornwell, S. E., Delellis, N. S., Kelly, D., Liu, Y., Mayhew, A., Chen, Y., & Rubin, V. L. (2025). Theorizing Improved NLP Features for Promoting Behavior that Supports CMC Users’ Subjective Well-Being. Proceedings of the Annual Conference of CAIS Actes Du congrès Annuel De l’ACSI. https://doi.org/10.29173/cais1937

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Section

Work in Progress / Recherche en cours